US7411606B2 - Efficient image categorization - Google Patents

Efficient image categorization Download PDF

Info

Publication number
US7411606B2
US7411606B2 US11/061,176 US6117605A US7411606B2 US 7411606 B2 US7411606 B2 US 7411606B2 US 6117605 A US6117605 A US 6117605A US 7411606 B2 US7411606 B2 US 7411606B2
Authority
US
United States
Prior art keywords
category
category level
user
highest
lowest
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Expired - Fee Related, expires
Application number
US11/061,176
Other versions
US20050140791A1 (en
Inventor
Eric C. Anderson
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Chemtron Research LLC
Original Assignee
FotoMedia Tech LLC
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by FotoMedia Tech LLC filed Critical FotoMedia Tech LLC
Priority to US11/061,176 priority Critical patent/US7411606B2/en
Publication of US20050140791A1 publication Critical patent/US20050140791A1/en
Priority to US11/176,808 priority patent/US7414651B2/en
Assigned to FLASHPOINT TECHNOLOGY, INC. reassignment FLASHPOINT TECHNOLOGY, INC. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: ANDERSON, ERIC C.
Assigned to IPAC ACQUISITION SUBSIDIARY I, LLC reassignment IPAC ACQUISITION SUBSIDIARY I, LLC ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: FLASHPOINT TECHNOLOGY, INC.
Assigned to FOTOMEDIA TECHNOLOGIES, LLC reassignment FOTOMEDIA TECHNOLOGIES, LLC ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: IPAC ACQUISITION SUBSIDIARY I, LLC
Publication of US7411606B2 publication Critical patent/US7411606B2/en
Application granted granted Critical
Assigned to FOTOMEDIA TECHNOLOGIES, LLC reassignment FOTOMEDIA TECHNOLOGIES, LLC ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: IPAC ACQUISITION SUBSIDIARY I, LLC
Assigned to KDL SCAN DESIGNS LLC reassignment KDL SCAN DESIGNS LLC ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: FOTOMEDIA TECHNOLOGIES, LLC
Assigned to CHEMTRON RESEARCH LLC reassignment CHEMTRON RESEARCH LLC MERGER (SEE DOCUMENT FOR DETAILS). Assignors: KDL SCAN DESIGNS LLC
Adjusted expiration legal-status Critical
Expired - Fee Related legal-status Critical Current

Links

Images

Classifications

    • GPHYSICS
    • G11INFORMATION STORAGE
    • G11BINFORMATION STORAGE BASED ON RELATIVE MOVEMENT BETWEEN RECORD CARRIER AND TRANSDUCER
    • G11B27/00Editing; Indexing; Addressing; Timing or synchronising; Monitoring; Measuring tape travel
    • G11B27/10Indexing; Addressing; Timing or synchronising; Measuring tape travel
    • G11B27/102Programmed access in sequence to addressed parts of tracks of operating record carriers
    • G11B27/105Programmed access in sequence to addressed parts of tracks of operating record carriers of operating discs
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/58Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually

Definitions

  • the present invention relates to categorizing digital images on a computer system, and more particularly, to a more efficient method for categorizing images and for reducing inconsistent terminology during categorization and searching.
  • PhotoSee ProTM by ACD Systems, for example, is an image management program that includes photo viewing functionality and a photo database for storing and retrieving thumbnail images from a photo CD.
  • the program allows a user to browse their entire photo collection without swapping photo CDs.
  • the program creates a thumbnail image for each photo found on the CD and allows the user to enter properties, such as caption, date, photographer, description, and keywords, for each thumbnail image. The user may then search the entire photo collection by entering desired properties.
  • the present invention addresses such a need.
  • the present invention provides a method for efficiently categorizing images on a computer system.
  • a series of related images that are to be categorized are ordered by time of capture, and category levels for input of category information by a user are displayed.
  • the category levels include a highest-category level and a lowest-category level, where the highest-category level has a low frequency of data change between the series of related images, and the lowest-category level has a high frequency of data change between the series of images.
  • a first image is then categorized by allowing the user to enter highest-category level data and lowest-category level data.
  • a next image in the series is then categorized by leaving the highest-category level data unchanged, and automatically selecting the lowest-category level data for reentry by the user, thereby eliminating the need for the user to reenter the highest-category level data.
  • a second aspect of the present invention provides a list key category terms available to categorize images.
  • the user selects particular terms from the list, and those terms are copied to a list of terms that will be used to categorize the current image.
  • that image will inherit the terms used for the previous images.
  • the present invention dramatically reduces the effort required to categorize a new or existing set of images that are related by subject matter.
  • the use of category lists greatly reduces errors in cataloging and searching because the lists ensure that the user uses consistent terminology when entering category information.
  • FIG. 1 is a block diagram illustrating an image categorization system.
  • FIG. 2 is a flow chart illustrating the process of categorizing images.
  • FIG. 3A is a block diagram illustrating a conceptual category form with hierarchical category levels.
  • FIG. 3B is a block diagram illustrating a specific example of a category form with hierarchical category levels.
  • FIG. 3C is a block diagram illustrating the category form.
  • FIG. 4 is a flow chart illustrating a process for minimizing inconsistent terminology.
  • FIG. 5 is a block diagram showing an example category form with category lists in accordance with a second embodiment of the present invention.
  • the present invention relates to efficiently categorizing images on a computer system.
  • the following description is presented to enable one of ordinary skill in the art to make and use the invention and is provided in the context of a patent application and its requirements.
  • Various modifications to the preferred embodiment and the generic principles and features described herein will be readily apparent to those skilled in the art.
  • the present invention is not intended to be limited to the embodiment shown but is to be accorded the widest scope consistent with the principles and features described herein.
  • the present invention takes advantage of the fact that images are taken as people move through life in a sequence of time, and the pictures are taken along that time line.
  • images are taken as people move through life in a sequence of time, and the pictures are taken along that time line.
  • a person who takes the camera to a birthday party may take multiple photographs of the party. Therefore, all the images taken during that photography session will be related by both time and subject matter.
  • pictures are usually taken in multiple sessions. For example, while on vacation in Greece, a tourist will take groups of pictures during different photography sessions (e.g., a series of images taken at a hotel, another series of images taken at a museum, another series of images taken at a beach, and so on). All the images taken while on vacation are related by the fact that they were taken in Greece, while all the photographs taken at the museum are related by the fact that they were taken at the museum in Greece, and so on.
  • the present invention provides automatic sequential categorization that takes advantage of the fact that photographs are related by time and subject matter, with the general principal being that the closer in time the images were taken, the higher the degree of subject matter correlation. Specifically, the assumption is made that when storing a set of images in a database, if the images are first ordered by date and time of capture and by source (camera and/or photographer), then the replication of data between images in the sequence may be automated. Thus, when categorizing a series of related digital images, the category information from one image is automatically inherited by the next image to reduce the amount of input required during the categorization process. Referring to the birthday party example, with the present invention, the information that each of the birthday photographs is classified as “friends,” “birthday,” “indoors,” does not have to be reentered for each image in the series, thereby saving the user time and effort.
  • FIG. 1 is a block diagram illustrating an image categorization system in a preferred embodiment of the present invention.
  • the system 10 includes a workstation or personal computer (PC) 12 , which is controlled by a keyboard 14 and a pointing device, such as a mouse 16 , and includes a display 20 .
  • Digital images to be categorized and stored may be input into the system from a variety of sources, such as a digital camera, a CD or DVD ROM, a disk, or a scanner, for instance.
  • a user then categorizes the images using an image management application 18 written in accordance with the present invention, which stores the images along with category information for later retrieval.
  • the images and category information may be stored locally on a PC storage device, such as a hard drive, CDR or writeable DVD, or high-capacity disk.
  • the images and category information may also be uploaded for storage on a Web-hosting photo site 40 via the Internet 42 .
  • the computer 12 and peripheral devices could be a dedicated box that displays the image management application 18 and the images on a display such as television, for instance.
  • FIG. 2 is a flow chart illustrating the process of categorizing images using an image management application 18 in accordance with the preferred embodiment of the present invention.
  • the process is implemented as an image management application 18 executed on a computer.
  • the process is implemented as the image management application 18 which is executed by a remote server and displayed on the computer's monitor 20 via a network, such as the Internet 42 .
  • the process is executed on a digital camera, or other hand-held image device, equipped with voice recognition and/or a stylus for input of the data.
  • the process for categorizing images begins by ordering a series of images to be categorized by time and date of capture in step 50 .
  • a form is then displayed that includes a series of hierarchical category levels for input of category information by the user in step 52 .
  • FIG. 3A is a block diagram illustrating a conceptual category form with hierarchical category levels.
  • the category levels 60 are displayed on a monitor 20 and preferably arranged from highest-category level 62 to lowest-category level 64 , with intermediate category levels 66 in-between.
  • Each category level 60 includes a corresponding field 68 for data entry by the user.
  • the hierarchical category levels 60 are used to represent levels of conceptual correlation between adjacent images. That is, the highest-category level 62 is used to represent high-level concepts pertaining to the images, and the lowest-category level 64 are used to represent detail-level concepts pertaining to the images. As a user moves from one image to the next during categorization, the data corresponding to the high-level concepts in the highest-category level 62 will change least frequently, while the data corresponding to low-level concepts in progressively lowest-category level 64 will change with progressively higher frequency. At the lowest-category level, it is assumed that there is virtually no correlation between adjacent images.
  • FIG. 3B is a block diagram illustrating an example of a category form having hierarchical category levels.
  • the category form 70 includes four category levels 60 , which may be user definable or set by default. Assume for example that a user visited various cities around the world and wishes to categorize the photographs. It is therefore appropriate that the images be categorized by the broad concept of “Trip” in the highest category-level, the names of the cities in the second highest category-level, called “Location”, the names of the locations within each city in the third highest category-level, called “Session”, and the details pertaining to each individual image in the lowest category-level, called “Caption”.
  • the category form 70 includes an area for displaying a thumbnail 72 of the current image.
  • the category form 70 may also include various function buttons, such as a play button 74 , a “Previous” button 76 , a “Next” button 77 , a “Done” button 78 , a “Cancel” button 79 .
  • the play button 74 plays any sound associated with the image
  • the “Previous” button 76 returns to the previous image
  • the “Next” button 77 goes to the next image
  • the “Done” button 78 saves all changes made and for exits
  • the “Cancel” button 79 cancels any changes made to the current image.
  • the user may enter data into the fields 68 of the hierarchical category levels 60 in order to categorize a current image in step 54 .
  • the data may be entered using any input means, such as a keyboard and/or by voice recognition.
  • the user has entered data for a current image belonging to a session of images captured at the Acropolis in Athens, Greece. Accordingly, the data entered for “Trip” is “Vacation in Greece”; the data entered for “Location” is “Athens”; the data entered for “Session” is “Acropolis”; and the data entered for “Caption” is “Parthenon”.
  • the next step in the processes is to categorize the next image in the series. In a preferred embodiment, this is done when the user clicks the “Next” button 77 , which applies the category data to the current image, and causes the thumbnail 72 for the next image to appear.
  • the data in the category level fields 68 is inherited from the previous image and is left unchanged on the display, and the lowest-category level is automatically selected for reentry by the user in step 56 .
  • FIG. 3C is a block diagram illustrating the category form 70 after the user has clicked the “Next” button 77 to categorize the next image in the sequence. All category fields 68 are left unchanged from the example shown in FIG. 3B , except the lowest-category level, “Caption”, which is selected for entry. The user may choose to leave the data unchanged (e.g., it is another photo of the Parthenon), or the user may change the data by entering a new “Caption”.
  • the user may change the data in the previous category level, “Session”, by pressing a key, such as the up arrow, or by clicking on the “Session” field. Successively pressing a key the key will move the cursor to successively higher category levels.
  • the “Next” button 77 the cursor will move to the lowest-category level field.
  • the present invention takes advantage of the fact that the images are ordered by date and time, and compares the date and time differences between adjacent images to automatically detect category changes from one image to the next. If a category change is detected, then the cursor is placed at the appropriate category level for the next image for reentry. For example, when the user finishes categorizing a current image and moves to the next, the date and time of the current image is compared with the date and time of the next image and the difference is compared to time thresholds. For example, a difference of one day may be used to indicate that the images were taken in different sessions. Therefore the cursor will automatically be moved one a level when the next image appears. A difference of one week may be used to indicate that the images were taken in different locations, and the cursor may be moved up two levels. A difference of one month may be used to indicate that the images were taken on different trips, so the cursor is moved to the top level.
  • the present invention saves the user an enormous amount of data entry time.
  • the user took a trip around the world, assume that the user visited twenty-five cities and took on average of five images in five different locations in each city, for a total of 625 images.
  • the user would have to enter the data into each of the four category level fields for each of the 625 images, for a total of 2500 entries (4 ⁇ 625).
  • the user only has to make 1 entry at the highest-category level, 5 entries at the second highest category-level, 125 entries at the third highest-category level, and 625 entries at the lowest-category level, for a total of 776 entries.
  • the present invention allows the user to categorize 625 images in the present example by entering just 1 ⁇ 3 the amount of data required by conventional programs.
  • caption information for the images in this example
  • the present invention is 3 times more efficient than prior methods.
  • the user would make 1875 entries (3 ⁇ 625) using conventional programs, but only 131 entries (1+25+125) with the present invention, which is 14 times more efficient. Therefore, using the conventional program, the user may spend a great deal of time entering information but only categorize 15 pictures out of the 625: whereas with the present invention, the user could categorize 210 pictures in the same amount of time.
  • the amount of overall efficiency gained, however, will depend on the number of images taken per session, the number of category levels, and the amount of correlation between the various levels. The more prolific a photographer is, the greater number images taken per session, and consequently the greater the increase in efficiency.
  • the user may search for particular images by entering category terms into a search form, and the application will display all images having matching keywords in step 58 .
  • the user enters key category terms into a single text box and the category application searches for matches in all category levels.
  • the category application then returns images ordered by the frequency of hits found, or by the number of hits found in the lowest-category level.
  • the user enters key category terms into one or more of the available category level fields, and only the images having matching key category words in the respective category levels are returned.
  • a user may categorize one image “Vacation in Japan”, and sometime later categorize a similar photo taken in Japan, “Trip to Japan”.
  • the search may not find the “Trip to Japan” image due to inconsistent terminology.
  • a second aspect of the present invention solves the problem of inconsistent terminology by allowing a user to choose predefined terms for entry into higher-level categories from a category list during image categorization.
  • category lists is that a predefined method of categorization exists; making it less likely that a similar image will be categorized differently and fail to show up in a subsequent search.
  • FIG. 4 is a flow chart illustrating a process for minimizing inconsistent terminology when categorizing a sequence of images in an image management system in accordance with the present invention.
  • the process begins by providing an available categories list containing predefined key category words in step 80 .
  • the use may then categorize a current image by moving selected key category terms from the available category lists to a current category list in step 82 .
  • FIG. 5 is a block diagram showing an illustrative category form 90 for categorizing a sequence of images using an available categories list and a current categories list, where like components from FIG. 3B have like reference numerals.
  • the available categories list 92 contains a listing of available predefined key category terms 94 , which were either entered by the user, or set by default by the system.
  • the current categories list 94 contains a listing of category terms that will be applied to the current image and inherited by the next image.
  • the user populates the current categories list 94 by selecting a key category term 96 from the available categories list 92 and then clicking the “Add” button to copy the term 96 to the current categories list 94 . The process is then repeated for each term 96 the user desires to be applied to the current image.
  • the key category terms in the current categories list are applied to the current image and saved along with the image in step 84 .
  • the next image in the sequence is then categorized by applying the key category terms from the current categories list 94 to the image in step 86 .
  • the user may temporarily deselect key category terms in the current categories list 94 , such that the terms are not applied to the current image, but are available to be applied to the sequence of images in step 88 .
  • the key category terms 98 in the current categories list 94 that are to be applied to the current image are displayed in bold font, while the temporarily deselected key category terms 100 are shown in normal font in parentheses.
  • the temporarily deselected key category terms 100 may be moved from the current categories list 94 to a third list (not shown).
  • the category lists 92 and 94 take advantage of the fact key category terms will not change that often between adjacent images in a sequence of related images, so only minor switching between the lists 92 and 94 is required by the user.
  • the category form 70 of FIG. 3B may be provided with an autotype feature. As the user types entries into the data fields 68 , the entries are compared with all previous entries into that field and when a match is found; the system automatically enters the previous entry into the field for the user, which reduces inconsistent terminology.
  • the user may perform a search for particular images.
  • a search form is displayed having the available categories list 92 and the current categories list 94 .
  • the user enters the search terms using the same procedure used for categorizing images, namely moving key category terms 96 from the available categories list 92 to the current categories list 94 .
  • the user can click a button to execute the search.

Abstract

A method for efficiently categorizing images on a computer system is disclosed. A series of related images that are to be categorized are ordered by time of capture, and category levels for input of category information by a user are displayed. The category levels include a highest-category level and a lowest-category level, where the highest-category level has a low frequency of data change between the series of related images, and the lowest-category level has a high frequency of data change between the series of images. A first image is then categorized by allowing the user to enter highest-category level data and lowest-category level data. A next image in the series is then categorized by leaving the highest-category level data unchanged, and automatically selecting the lowest-category level data for reentry by the user, thereby eliminating the need for the user to reenter the highest-category level data.

Description

The present invention is a continuation of U.S. application Ser. No. 09/502,378, filed on Feb. 11, 2000, now U.S. Pat. No. 6,862,038, and entitled “Efficient Image Categorization.”
FIELD OF THE INVENTION
The present invention relates to categorizing digital images on a computer system, and more particularly, to a more efficient method for categorizing images and for reducing inconsistent terminology during categorization and searching.
BACKGROUND OF THE INVENTION
As digital photography and the digitization of old photographs become more and more prevalent, the number of digital images that are stored and archived will increase dramatically. Whether the digital images are stored locally on a user's PC or uploaded and stored on a Web photo-hosting site, the number of images will make it increasingly difficult for a user to find desired images.
To alleviate this problem, PC applications are available today that allow a user to categorize images. PhotoSee Pro™, by ACD Systems, for example, is an image management program that includes photo viewing functionality and a photo database for storing and retrieving thumbnail images from a photo CD. The program allows a user to browse their entire photo collection without swapping photo CDs. The program creates a thumbnail image for each photo found on the CD and allows the user to enter properties, such as caption, date, photographer, description, and keywords, for each thumbnail image. The user may then search the entire photo collection by entering desired properties.
Although programs such as PhotoSee Pro, and image database programs in general, allow the categorization of images using multiple categories, these programs have a major drawback. The problem is that in order to categorize the images, the user must retype the category information for each image. When categorizing a photo CD having a large amount of images, manually entering category information for each image is extremely tedious and time-consuming for the user. The problem is even worse for users who have a large collection of photo CDs or scanned images that they wish to electronically archive.
What is needed is a more efficient method for categorizing digital images. The present invention addresses such a need.
SUMMARY OF THE INVENTION
The present invention provides a method for efficiently categorizing images on a computer system is disclosed. A series of related images that are to be categorized are ordered by time of capture, and category levels for input of category information by a user are displayed. The category levels include a highest-category level and a lowest-category level, where the highest-category level has a low frequency of data change between the series of related images, and the lowest-category level has a high frequency of data change between the series of images. A first image is then categorized by allowing the user to enter highest-category level data and lowest-category level data. A next image in the series is then categorized by leaving the highest-category level data unchanged, and automatically selecting the lowest-category level data for reentry by the user, thereby eliminating the need for the user to reenter the highest-category level data.
A second aspect of the present invention provides a list key category terms available to categorize images. To categorize a current image, the user selects particular terms from the list, and those terms are copied to a list of terms that will be used to categorize the current image. When the next image is to be categorized, that image will inherit the terms used for the previous images.
Thus, the present invention dramatically reduces the effort required to categorize a new or existing set of images that are related by subject matter. In addition, the use of category lists greatly reduces errors in cataloging and searching because the lists ensure that the user uses consistent terminology when entering category information.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is a block diagram illustrating an image categorization system.
FIG. 2 is a flow chart illustrating the process of categorizing images.
FIG. 3A is a block diagram illustrating a conceptual category form with hierarchical category levels.
FIG. 3B is a block diagram illustrating a specific example of a category form with hierarchical category levels.
FIG. 3C is a block diagram illustrating the category form.
FIG. 4 is a flow chart illustrating a process for minimizing inconsistent terminology.
FIG. 5 is a block diagram showing an example category form with category lists in accordance with a second embodiment of the present invention.
DESCRIPTION OF THE INVENTION
The present invention relates to efficiently categorizing images on a computer system. The following description is presented to enable one of ordinary skill in the art to make and use the invention and is provided in the context of a patent application and its requirements. Various modifications to the preferred embodiment and the generic principles and features described herein will be readily apparent to those skilled in the art. Thus, the present invention is not intended to be limited to the embodiment shown but is to be accorded the widest scope consistent with the principles and features described herein.
The present invention takes advantage of the fact that images are taken as people move through life in a sequence of time, and the pictures are taken along that time line. Thus, there is typically a high degree of correlation between images that are captured during a typical photography session. For example, a person who takes the camera to a birthday party may take multiple photographs of the party. Therefore, all the images taken during that photography session will be related by both time and subject matter. While on vacation, pictures are usually taken in multiple sessions. For example, while on vacation in Greece, a tourist will take groups of pictures during different photography sessions (e.g., a series of images taken at a hotel, another series of images taken at a museum, another series of images taken at a beach, and so on). All the images taken while on vacation are related by the fact that they were taken in Greece, while all the photographs taken at the museum are related by the fact that they were taken at the museum in Greece, and so on.
The problem is that since all the photographs are related, information required to categorize the photographs in a database must also be replicated, which is time-consuming and tedious to the user.
The present invention provides automatic sequential categorization that takes advantage of the fact that photographs are related by time and subject matter, with the general principal being that the closer in time the images were taken, the higher the degree of subject matter correlation. Specifically, the assumption is made that when storing a set of images in a database, if the images are first ordered by date and time of capture and by source (camera and/or photographer), then the replication of data between images in the sequence may be automated. Thus, when categorizing a series of related digital images, the category information from one image is automatically inherited by the next image to reduce the amount of input required during the categorization process. Referring to the birthday party example, with the present invention, the information that each of the birthday photographs is classified as “friends,” “birthday,” “indoors,” does not have to be reentered for each image in the series, thereby saving the user time and effort.
FIG. 1 is a block diagram illustrating an image categorization system in a preferred embodiment of the present invention. The system 10 includes a workstation or personal computer (PC) 12, which is controlled by a keyboard 14 and a pointing device, such as a mouse 16, and includes a display 20. Digital images to be categorized and stored may be input into the system from a variety of sources, such as a digital camera, a CD or DVD ROM, a disk, or a scanner, for instance.
A user then categorizes the images using an image management application 18 written in accordance with the present invention, which stores the images along with category information for later retrieval. The images and category information may be stored locally on a PC storage device, such as a hard drive, CDR or writeable DVD, or high-capacity disk. The images and category information may also be uploaded for storage on a Web-hosting photo site 40 via the Internet 42. It should also be readily understood that the computer 12 and peripheral devices could be a dedicated box that displays the image management application 18 and the images on a display such as television, for instance.
FIG. 2 is a flow chart illustrating the process of categorizing images using an image management application 18 in accordance with the preferred embodiment of the present invention. As stated above, in one preferred embodiment, the process is implemented as an image management application 18 executed on a computer. In a second preferred embodiment, the process is implemented as the image management application 18 which is executed by a remote server and displayed on the computer's monitor 20 via a network, such as the Internet 42. In a third preferred embodiment, the process is executed on a digital camera, or other hand-held image device, equipped with voice recognition and/or a stylus for input of the data.
The process for categorizing images begins by ordering a series of images to be categorized by time and date of capture in step 50. A form is then displayed that includes a series of hierarchical category levels for input of category information by the user in step 52.
FIG. 3A is a block diagram illustrating a conceptual category form with hierarchical category levels. The category levels 60 are displayed on a monitor 20 and preferably arranged from highest-category level 62 to lowest-category level 64, with intermediate category levels 66 in-between. Each category level 60 includes a corresponding field 68 for data entry by the user.
According to the present invention, the hierarchical category levels 60 are used to represent levels of conceptual correlation between adjacent images. That is, the highest-category level 62 is used to represent high-level concepts pertaining to the images, and the lowest-category level 64 are used to represent detail-level concepts pertaining to the images. As a user moves from one image to the next during categorization, the data corresponding to the high-level concepts in the highest-category level 62 will change least frequently, while the data corresponding to low-level concepts in progressively lowest-category level 64 will change with progressively higher frequency. At the lowest-category level, it is assumed that there is virtually no correlation between adjacent images.
FIG. 3B is a block diagram illustrating an example of a category form having hierarchical category levels. In this example, the category form 70 includes four category levels 60, which may be user definable or set by default. Assume for example that a user visited various cities around the world and wishes to categorize the photographs. It is therefore appropriate that the images be categorized by the broad concept of “Trip” in the highest category-level, the names of the cities in the second highest category-level, called “Location”, the names of the locations within each city in the third highest category-level, called “Session”, and the details pertaining to each individual image in the lowest category-level, called “Caption”.
In a preferred embodiment, the category form 70 includes an area for displaying a thumbnail 72 of the current image. The category form 70 may also include various function buttons, such as a play button 74, a “Previous” button 76, a “Next” button 77, a “Done” button 78, a “Cancel” button 79. The play button 74 plays any sound associated with the image, the “Previous” button 76 returns to the previous image, the “Next” button 77 goes to the next image, the “Done” button 78 saves all changes made and for exits, and the “Cancel” button 79 cancels any changes made to the current image.
Referring again to FIG. 2, after the category form 70 is displayed, the user may enter data into the fields 68 of the hierarchical category levels 60 in order to categorize a current image in step 54. The data may be entered using any input means, such as a keyboard and/or by voice recognition.
Referring to FIG. 3B for example, the user has entered data for a current image belonging to a session of images captured at the Acropolis in Athens, Greece. Accordingly, the data entered for “Trip” is “Vacation in Greece”; the data entered for “Location” is “Athens”; the data entered for “Session” is “Acropolis”; and the data entered for “Caption” is “Parthenon”.
Referring to both FIGS. 2 and 3B, after entering the category data, the next step in the processes is to categorize the next image in the series. In a preferred embodiment, this is done when the user clicks the “Next” button 77, which applies the category data to the current image, and causes the thumbnail 72 for the next image to appear. According to the present invention, the data in the category level fields 68 is inherited from the previous image and is left unchanged on the display, and the lowest-category level is automatically selected for reentry by the user in step 56.
FIG. 3C is a block diagram illustrating the category form 70 after the user has clicked the “Next” button 77 to categorize the next image in the sequence. All category fields 68 are left unchanged from the example shown in FIG. 3B, except the lowest-category level, “Caption”, which is selected for entry. The user may choose to leave the data unchanged (e.g., it is another photo of the Parthenon), or the user may change the data by entering a new “Caption”.
If the current image to be categorized was photographed in a different session than the previous image, then the user may change the data in the previous category level, “Session”, by pressing a key, such as the up arrow, or by clicking on the “Session” field. Successively pressing a key the key will move the cursor to successively higher category levels. When the user clicks the “Next” button 77, the cursor will move to the lowest-category level field.
In a preferred embodiment, however, the present invention takes advantage of the fact that the images are ordered by date and time, and compares the date and time differences between adjacent images to automatically detect category changes from one image to the next. If a category change is detected, then the cursor is placed at the appropriate category level for the next image for reentry. For example, when the user finishes categorizing a current image and moves to the next, the date and time of the current image is compared with the date and time of the next image and the difference is compared to time thresholds. For example, a difference of one day may be used to indicate that the images were taken in different sessions. Therefore the cursor will automatically be moved one a level when the next image appears. A difference of one week may be used to indicate that the images were taken in different locations, and the cursor may be moved up two levels. A difference of one month may be used to indicate that the images were taken on different trips, so the cursor is moved to the top level.
During normal categorization, most images will be related at the session level. Therefore, most adjacent images in a series will not require any change to the category data except at the lowest-category level. Thus, the present invention saves the user an enormous amount of data entry time. In the example where the user took a trip around the world, assume that the user visited twenty-five cities and took on average of five images in five different locations in each city, for a total of 625 images.
Using a conventional program, such as PhotoSee Pro, the user would have to enter the data into each of the four category level fields for each of the 625 images, for a total of 2500 entries (4×625). With the present invention in contrast, the user only has to make 1 entry at the highest-category level, 5 entries at the second highest category-level, 125 entries at the third highest-category level, and 625 entries at the lowest-category level, for a total of 776 entries.
Thus, the present invention allows the user to categorize 625 images in the present example by entering just ⅓ the amount of data required by conventional programs. When entering caption information for the images in this example, the present invention is 3 times more efficient than prior methods. Notice that if the user does not enter the caption information, the user would make 1875 entries (3×625) using conventional programs, but only 131 entries (1+25+125) with the present invention, which is 14 times more efficient. Therefore, using the conventional program, the user may spend a great deal of time entering information but only categorize 15 pictures out of the 625: whereas with the present invention, the user could categorize 210 pictures in the same amount of time. The amount of overall efficiency gained, however, will depend on the number of images taken per session, the number of category levels, and the amount of correlation between the various levels. The more prolific a photographer is, the greater number images taken per session, and consequently the greater the increase in efficiency.
Referring again to FIG. 2, after categorization a series of images, the user may search for particular images by entering category terms into a search form, and the application will display all images having matching keywords in step 58. In one preferred embodiment, the user enters key category terms into a single text box and the category application searches for matches in all category levels. The category application then returns images ordered by the frequency of hits found, or by the number of hits found in the lowest-category level. In a second preferred embodiment, the user enters key category terms into one or more of the available category level fields, and only the images having matching key category words in the respective category levels are returned.
A problem frequently encountered when searching images, and for database searching in general, is that the user may use different terms when categorizing similar photos. Similarly, the user may use different terms to search for an image than the terms used to categorize the image.
For example, a user may categorize one image “Vacation in Japan”, and sometime later categorize a similar photo taken in Japan, “Trip to Japan”. When performing a subsequent search to find all “Vacation” images, the search may not find the “Trip to Japan” image due to inconsistent terminology.
A second aspect of the present invention solves the problem of inconsistent terminology by allowing a user to choose predefined terms for entry into higher-level categories from a category list during image categorization. The advantage of category lists is that a predefined method of categorization exists; making it less likely that a similar image will be categorized differently and fail to show up in a subsequent search.
FIG. 4 is a flow chart illustrating a process for minimizing inconsistent terminology when categorizing a sequence of images in an image management system in accordance with the present invention. The process begins by providing an available categories list containing predefined key category words in step 80. The use may then categorize a current image by moving selected key category terms from the available category lists to a current category list in step 82.
FIG. 5 is a block diagram showing an illustrative category form 90 for categorizing a sequence of images using an available categories list and a current categories list, where like components from FIG. 3B have like reference numerals. The available categories list 92 contains a listing of available predefined key category terms 94, which were either entered by the user, or set by default by the system. The current categories list 94 contains a listing of category terms that will be applied to the current image and inherited by the next image. The user populates the current categories list 94 by selecting a key category term 96 from the available categories list 92 and then clicking the “Add” button to copy the term 96 to the current categories list 94. The process is then repeated for each term 96 the user desires to be applied to the current image.
Referring to both FIGS. 4 and 5, after the user has populated the current categories list 94, the user clicks the “Next” button 77 to categorize the next image in the sequence, the key category terms in the current categories list are applied to the current image and saved along with the image in step 84. The next image in the sequence is then categorized by applying the key category terms from the current categories list 94 to the image in step 86.
Before the terms are applied, the user may temporarily deselect key category terms in the current categories list 94, such that the terms are not applied to the current image, but are available to be applied to the sequence of images in step 88. In a preferred embodiment, the key category terms 98 in the current categories list 94 that are to be applied to the current image are displayed in bold font, while the temporarily deselected key category terms 100 are shown in normal font in parentheses. Alternatively, the temporarily deselected key category terms 100 may be moved from the current categories list 94 to a third list (not shown).
According to the present invention, the category lists 92 and 94 take advantage of the fact key category terms will not change that often between adjacent images in a sequence of related images, so only minor switching between the lists 92 and 94 is required by the user.
In a third embodiment, rather than displaying key category terms 96 in the available categories list 92, the category form 70 of FIG. 3B may be provided with an autotype feature. As the user types entries into the data fields 68, the entries are compared with all previous entries into that field and when a match is found; the system automatically enters the previous entry into the field for the user, which reduces inconsistent terminology.
After all the images have been categorized, the user may perform a search for particular images. In a preferred embodiment, a search form is displayed having the available categories list 92 and the current categories list 94. The user enters the search terms using the same procedure used for categorizing images, namely moving key category terms 96 from the available categories list 92 to the current categories list 94. Once the desired terms 96 have been chosen, the user can click a button to execute the search.
An efficient method for categorizing a sequence of images has been disclosed. The combined use of the principles disclosed herein will dramatically reduce the effort to categorize a new or existing set of images that are related by subject matter, which is typically a natural consequence of photography.
The present invention has been described in accordance with the embodiments shown, and one of ordinary skill in the art will readily recognize that there could be variations to the embodiments, and any variations are would be within the spirit and scope of the present invention. Accordingly, many modifications may be made by one of ordinary skill in the art without departing from the spirit and scope of the appended claims.

Claims (20)

1. A method for efficiently categorizing images on a computer system, comprising:
ordering a series of related images that are to be categorized by time of capture;
displaying a user interface with data entry fields corresponding to category levels for input of category information by a user, wherein the category levels include a highest-category level and a lowest-category level, the highest-category level having a low frequency of data change between the series of related images, and the lowest-category level having a high frequency of data change between the series of related images;
categorizing a first image by allowing the user to enter, via the highest-category level data entry field, highest-category level data and, via the lowest-category level data entry field, lowest-category level data; and
categorizing a next image in the series by automatically determining based on the image's time of capture whether to initiate user data entry in the highest-category level data entry field or the lowest-category level data entry field.
2. The method of claim 1 wherein categorizing a next image includes comparing date and time differences between the first image and the next image.
3. The method of claim 1 further including:
in response to a user pressing a key, moving a cursor from the lowest-category level data entry field to a higher-category level data entry field for data entry.
4. The method of claim 1 further including:
categorizing another image in the series by leaving the cursor at the higher-category level data entry field for data entry.
5. The method of claim 1 wherein displaying category levels further includes the step of:
displaying an intermediate category level data entry field having medium frequency of data change between the series of related images.
6. The method of claim 1 comprising displaying a thumbnail of the current image being categorized.
7. A method for efficiently categorizing images on a computer system, comprising:
ordering a series of related images that are to be categorized by time of capture;
displaying category levels for input of category information by a user, wherein the category levels include a highest-category level and a lowest-category level, the highest-category level having a low frequency of data change between the series of related images, and the lowest-category level having a high frequency of data change between the series of related images;
categorizing a first image by allowing the user to enter highest-category level data and lowest-category level data;
categorizing a next image in the series by leaving the highest-category level data unchanged, and automatically selecting the lowest-category level data for reentry by the user, thereby eliminating the need for the user to reenter the highest-category level data; and
as the user enters data, comparing the data with previous entries, and when a match is found, automatically entering the previous entry to thereby reduce inconsistent terminology.
8. A system for efficiently categorization digital images, comprising:
input means for receiving a series of digital images;
a display;
a computer;
interface means for a user to operate the computer;
storage means for storing the digital images; and
an image management application executed by the computer, wherein the image management application includes means for:
ordering a series of related images that are to be categorized by time of capture;
displaying a user interface with data entry fields corresponding to category levels for input of category information by a user, wherein the category levels include a highest-category level and a lowest-category level, the highest-category level having a low frequency of data change between the series of related images, and the lowest-category level having a high frequency of data change between the series of related images;
categorizing a first image by allowing the user to enter, via the highest-category level data entry field, highest-category level data and, via the lowest-category level data entry field, lowest-category level data; and
categorizing a next image in the series by automatically determining based on the image's time of capture whether to initiate user data entry in the highest-category level data entry field or the lowest-category level data entry field.
9. The system of claim 8 wherein the image management application compares date and time differences between the first image and the next image.
10. The system of claim 8 wherein the computer comprises a web server that is remote from the display and interface means.
11. The system of claim 8 wherein the display is a television.
12. The system of claim 8 wherein the interface means comprises a keyboard and a mouse.
13. The system of claim 8 wherein the interface means comprises voice recognition.
14. A computer readable medium embodying computer program instructions for efficiently categorizing images on a computer system, the instructions for:
ordering a series of related images that are to be categorized by time of capture;
displaying a user interface with data entry fields corresponding to category levels for input of category information by a user, wherein the category levels include a highest-category level and a lowest-category level, the highest-category level having a low frequency of data change between the series of related images, and the lowest-category level having a high frequency of data change between the series of related images;
categorizing a first image by allowing the user to enter, via the highest-category level data entry field, highest-category level data and, via the lowest-category level data entry field, lowest-category level data; and
categorizing a next image in the series by automatically determining based on the image's time of capture whether to initiate user data entry in the highest-category level data entry field or the lowest-category level data entry field.
15. The method of claim 14 comprising instructions for: comparing date and time differences between the first image and the next image.
16. The computer readable medium of claim 14 further including the instruction of:
in response to a user pressing a key, moving a cursor from the lowest-category level data entry field to a higher-category level data entry field for data entry.
17. The computer readable medium of claim 14 comprising instructions for categorizing another image in the series by leaving the cursor at the higher-category level data entry field for data entry.
18. The computer readable medium of claim 14 comprising instructions for displaying an intermediate category level data entry field having medium frequency of data change between the series of related images.
19. The computer readable medium of claim 14 comprising instructions for displaying a thumbnail of the current image being categorized.
20. A computer readable medium embodying computer program instructions for efficiently categorizing images on a computer system, the instructions for:
ordering a series of related images that are to be categorized by time of capture;
displaying category levels for input of category information by a user, wherein the category levels include a highest-category level and a lowest-category level, the highest-category level having a low frequency of data change between the series of related images, and the lowest-category level having a high frequency of data change between the series of related images;
categorizing a first image by allowing the user to enter highest-category level data and lowest-category level data;
categorizing a next image in the series by leaving the highest-category level data unchanged, and automatically selecting the lowest-category level data for reentry by the user, thereby eliminating the need for the user to reenter the highest-category level data; and
as the user enters data, comparing the data with previous entries, and when a match is found, automatically entering the previous entry to thereby reduce inconsistent terminology.
US11/061,176 2000-02-11 2005-02-18 Efficient image categorization Expired - Fee Related US7411606B2 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
US11/061,176 US7411606B2 (en) 2000-02-11 2005-02-18 Efficient image categorization
US11/176,808 US7414651B2 (en) 2000-02-11 2005-07-06 Efficient image categorization

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US09/502,378 US6862038B1 (en) 2000-02-11 2000-02-11 Efficient image categorization
US11/061,176 US7411606B2 (en) 2000-02-11 2005-02-18 Efficient image categorization

Related Parent Applications (1)

Application Number Title Priority Date Filing Date
US09/502,378 Continuation US6862038B1 (en) 2000-02-11 2000-02-11 Efficient image categorization

Related Child Applications (1)

Application Number Title Priority Date Filing Date
US11/176,808 Division US7414651B2 (en) 2000-02-11 2005-07-06 Efficient image categorization

Publications (2)

Publication Number Publication Date
US20050140791A1 US20050140791A1 (en) 2005-06-30
US7411606B2 true US7411606B2 (en) 2008-08-12

Family

ID=34193382

Family Applications (3)

Application Number Title Priority Date Filing Date
US09/502,378 Expired - Lifetime US6862038B1 (en) 2000-02-11 2000-02-11 Efficient image categorization
US11/061,176 Expired - Fee Related US7411606B2 (en) 2000-02-11 2005-02-18 Efficient image categorization
US11/176,808 Expired - Lifetime US7414651B2 (en) 2000-02-11 2005-07-06 Efficient image categorization

Family Applications Before (1)

Application Number Title Priority Date Filing Date
US09/502,378 Expired - Lifetime US6862038B1 (en) 2000-02-11 2000-02-11 Efficient image categorization

Family Applications After (1)

Application Number Title Priority Date Filing Date
US11/176,808 Expired - Lifetime US7414651B2 (en) 2000-02-11 2005-07-06 Efficient image categorization

Country Status (1)

Country Link
US (3) US6862038B1 (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090248703A1 (en) * 2008-03-26 2009-10-01 Fujifilm Corporation Saving device for image sharing, image sharing system, and image sharing method

Families Citing this family (31)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6862038B1 (en) * 2000-02-11 2005-03-01 Ipac Acquisition Subsidiary I, Llc Efficient image categorization
JP3622620B2 (en) * 2000-02-18 2005-02-23 富士写真フイルム株式会社 Image information acquisition method, image information transmission apparatus, and image information transmission system
JP4124402B2 (en) * 2000-03-31 2008-07-23 株式会社リコー Image input device
US7032182B2 (en) * 2000-12-20 2006-04-18 Eastman Kodak Company Graphical user interface adapted to allow scene content annotation of groups of pictures in a picture database to promote efficient database browsing
US7840634B2 (en) * 2001-06-26 2010-11-23 Eastman Kodak Company System and method for managing images over a communication network
US7184082B2 (en) * 2001-08-28 2007-02-27 Olympus Corporation Image displaying system, image displaying method, image printing system, and image printing method
US7009643B2 (en) * 2002-03-15 2006-03-07 Canon Kabushiki Kaisha Automatic determination of image storage location
JP2003298991A (en) * 2002-03-29 2003-10-17 Fuji Photo Film Co Ltd Image arranging method and apparatus, and program
JP4093544B2 (en) * 2002-06-19 2008-06-04 カシオ計算機株式会社 IMAGING DEVICE, ALBUM FILE CREATION METHOD AND ALBUM FILE CREATION PROGRAM IN IMAGING DEVICE
US20040006577A1 (en) * 2002-07-02 2004-01-08 Malcolm Rix Method for managing media files
JP4329893B2 (en) * 2002-07-15 2009-09-09 株式会社リコー Digital camera device
US7327347B2 (en) * 2002-12-23 2008-02-05 Fuji Xerox Co., Ltd. Image classifying systems and methods
JP2004234228A (en) * 2003-01-29 2004-08-19 Seiko Epson Corp Image search device, keyword assignment method in image search device, and program
US20050166149A1 (en) * 2004-01-23 2005-07-28 Microsoft Corporation Table of contents display
JP4708733B2 (en) * 2004-05-21 2011-06-22 キヤノン株式会社 Imaging device
US8456488B2 (en) * 2004-10-06 2013-06-04 Apple Inc. Displaying digital images using groups, stacks, and version sets
US7557818B1 (en) * 2004-10-06 2009-07-07 Apple Inc. Viewing digital images using a floating controller
US7705858B2 (en) * 2004-10-06 2010-04-27 Apple Inc. Techniques for displaying digital images on a display
US7945535B2 (en) * 2004-12-13 2011-05-17 Microsoft Corporation Automatic publishing of digital content
KR101133125B1 (en) * 2005-06-23 2012-04-06 삼성테크윈 주식회사 A system and method to display filming time
US20070032887A1 (en) * 2005-07-26 2007-02-08 Brother Kogyo Kabushiki Kaisha Information management system, information processing device, and program
US7796837B2 (en) * 2005-09-22 2010-09-14 Google Inc. Processing an image map for display on computing device
KR101162171B1 (en) * 2005-09-22 2012-07-02 엘지전자 주식회사 mobile communication terminal taking moving image and its operating method
JP4577173B2 (en) * 2005-09-29 2010-11-10 ソニー株式会社 Information processing apparatus and method, and program
JP2007097076A (en) * 2005-09-30 2007-04-12 Fujifilm Corp Photographic time correction apparatus, photographic time correction method and program
JP4850645B2 (en) * 2006-09-14 2012-01-11 キヤノン株式会社 Image reproducing apparatus and image reproducing method
US8615112B2 (en) * 2007-03-30 2013-12-24 Casio Computer Co., Ltd. Image pickup apparatus equipped with face-recognition function
JP4834639B2 (en) * 2007-09-28 2011-12-14 株式会社東芝 Electronic device and image display control method
JP4834640B2 (en) * 2007-09-28 2011-12-14 株式会社東芝 Electronic device and image display control method
US8775953B2 (en) 2007-12-05 2014-07-08 Apple Inc. Collage display of image projects
JP2014229282A (en) * 2013-05-27 2014-12-08 キヤノン株式会社 Image retrieval device, image retrieval method, system, program and storage medium

Citations (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5796428A (en) 1993-10-21 1998-08-18 Hitachi, Ltd. Electronic photography system
US5845166A (en) 1997-02-20 1998-12-01 Eastman Kodak Company Hybrid camera with identification matching of film and electronic images
JPH11184605A (en) * 1997-12-24 1999-07-09 Toshiba Corp Data input device, cursor control method and recording medium
US5940121A (en) 1997-02-20 1999-08-17 Eastman Kodak Company Hybrid camera system with electronic album control
US6005679A (en) * 1994-08-22 1999-12-21 Fuji Photo Film Co., Ltd. Image data filing system for quickly retrieving an area of interest of an image from a reduced amount of image data
US6097389A (en) * 1997-10-24 2000-08-01 Pictra, Inc. Methods and apparatuses for presenting a collection of digital media in a media container
US6237010B1 (en) * 1997-10-06 2001-05-22 Canon Kabushiki Kaisha Multimedia application using flashpix file format
US6335742B1 (en) * 1997-07-24 2002-01-01 Ricoh Company, Ltd. Apparatus for file management and manipulation using graphical displays and textual descriptions
US6462778B1 (en) 1999-02-26 2002-10-08 Sony Corporation Methods and apparatus for associating descriptive data with digital image files
US6603489B1 (en) * 2000-02-09 2003-08-05 International Business Machines Corporation Electronic calendaring system that automatically predicts calendar entries based upon previous activities
US6650826B1 (en) * 1998-04-02 2003-11-18 Sony Corporation Editing apparatus and method, and image material selection apparatus and method
US7032182B2 (en) * 2000-12-20 2006-04-18 Eastman Kodak Company Graphical user interface adapted to allow scene content annotation of groups of pictures in a picture database to promote efficient database browsing

Family Cites Families (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5761655A (en) * 1990-06-06 1998-06-02 Alphatronix, Inc. Image file storage and retrieval system
US5752193A (en) * 1995-09-01 1998-05-12 Motorola, Inc. Method and apparatus for communicating in a wireless communication system
US6075779A (en) * 1997-06-09 2000-06-13 Lucent Technologies, Inc. Random access channel congestion control for broadcast teleservice acknowledgment messages
US6597392B1 (en) * 1997-10-14 2003-07-22 Healthcare Vision, Inc. Apparatus and method for computerized multi-media data organization and transmission
US6236400B1 (en) * 1998-04-02 2001-05-22 Sun Microsystems, Inc. Method and apparatus for controlling the display of hierarchical information
US6366779B1 (en) * 1998-09-22 2002-04-02 Qualcomm Incorporated Method and apparatus for rapid assignment of a traffic channel in digital cellular communication systems
US6614772B1 (en) * 1999-03-01 2003-09-02 Nokia Corporation Method, and associated apparatus, for communicating packet data in a radio communication system
US6721299B1 (en) * 1999-03-15 2004-04-13 Lg Information & Communications, Ltd. Pilot signals for synchronization and/or channel estimation
US6574267B1 (en) * 1999-03-22 2003-06-03 Golden Bridge Technology, Inc. Rach ramp-up acknowledgement
US6862038B1 (en) * 2000-02-11 2005-03-01 Ipac Acquisition Subsidiary I, Llc Efficient image categorization

Patent Citations (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5796428A (en) 1993-10-21 1998-08-18 Hitachi, Ltd. Electronic photography system
US6005679A (en) * 1994-08-22 1999-12-21 Fuji Photo Film Co., Ltd. Image data filing system for quickly retrieving an area of interest of an image from a reduced amount of image data
US5845166A (en) 1997-02-20 1998-12-01 Eastman Kodak Company Hybrid camera with identification matching of film and electronic images
US5940121A (en) 1997-02-20 1999-08-17 Eastman Kodak Company Hybrid camera system with electronic album control
US6335742B1 (en) * 1997-07-24 2002-01-01 Ricoh Company, Ltd. Apparatus for file management and manipulation using graphical displays and textual descriptions
US6237010B1 (en) * 1997-10-06 2001-05-22 Canon Kabushiki Kaisha Multimedia application using flashpix file format
US6097389A (en) * 1997-10-24 2000-08-01 Pictra, Inc. Methods and apparatuses for presenting a collection of digital media in a media container
JPH11184605A (en) * 1997-12-24 1999-07-09 Toshiba Corp Data input device, cursor control method and recording medium
US6650826B1 (en) * 1998-04-02 2003-11-18 Sony Corporation Editing apparatus and method, and image material selection apparatus and method
US6462778B1 (en) 1999-02-26 2002-10-08 Sony Corporation Methods and apparatus for associating descriptive data with digital image files
US6603489B1 (en) * 2000-02-09 2003-08-05 International Business Machines Corporation Electronic calendaring system that automatically predicts calendar entries based upon previous activities
US7032182B2 (en) * 2000-12-20 2006-04-18 Eastman Kodak Company Graphical user interface adapted to allow scene content annotation of groups of pictures in a picture database to promote efficient database browsing

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
ACD Systems website printout.

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090248703A1 (en) * 2008-03-26 2009-10-01 Fujifilm Corporation Saving device for image sharing, image sharing system, and image sharing method
US8224824B2 (en) * 2008-03-26 2012-07-17 Fujifilm Corporation Saving device for image sharing, image sharing system, and image sharing method
US8538968B2 (en) 2008-03-26 2013-09-17 Fujifilm Corporation Saving device for image sharing, image sharing system, and image sharing method

Also Published As

Publication number Publication date
US7414651B2 (en) 2008-08-19
US20050140791A1 (en) 2005-06-30
US20050243188A1 (en) 2005-11-03
US6862038B1 (en) 2005-03-01

Similar Documents

Publication Publication Date Title
US7411606B2 (en) Efficient image categorization
US7542994B2 (en) Graphical user interface for rapid image categorization
US8701022B2 (en) Method and system for archiving and retrieving items based on episodic memory of groups of people
US6538698B1 (en) Method and system for sorting images in an image capture unit to ease browsing access
US8099679B2 (en) Method and system for traversing digital records with multiple dimensional attributes
JP3738212B2 (en) How to add personalized metadata to a collection of digital images
US8607166B2 (en) Browsing or searching user interfaces and other aspects
JP4791288B2 (en) Method and system for linking digital photographs to electronic documents
US20040135815A1 (en) Method and apparatus for image metadata entry
US7051048B2 (en) Data management system, data management method, and program
US20040111415A1 (en) Automatic organization of images uploaded to a photo-sharing site
CN107704519B (en) User side photo album management system based on cloud computing technology and interaction method thereof
JP2000276484A (en) Device and method for image retrieval and image display device
US20040168118A1 (en) Interactive media frame display
US20030088582A1 (en) Visual history multi-media database software
US20040064455A1 (en) Software-floating palette for annotation of images that are viewable in a variety of organizational structures
US20080208922A1 (en) Image metadata action tagging
JP2002010178A (en) Image managing system and method for managing image as well as storage medium
US20090083642A1 (en) Method for providing graphic user interface (gui) to display other contents related to content being currently generated, and a multimedia apparatus applying the same
Hjelsvold et al. Integrated video archive tools
JP2005301889A (en) Image comparison program
JPH0765021A (en) Information retrieving device
JP3994188B2 (en) Multimedia data search system, multimedia search method, and program for realizing the search method
JP2007207031A (en) Image processing device, image processing method, and image processing program
US6792417B1 (en) Information processing apparatus and method for storing and managing objects together with additional information

Legal Events

Date Code Title Description
AS Assignment

Owner name: FLASHPOINT TECHNOLOGY, INC., CALIFORNIA

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:ANDERSON, ERIC C.;REEL/FRAME:018086/0712

Effective date: 20000210

AS Assignment

Owner name: IPAC ACQUISITION SUBSIDIARY I, LLC, NEW HAMPSHIRE

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:FLASHPOINT TECHNOLOGY, INC.;REEL/FRAME:018094/0862

Effective date: 20020614

AS Assignment

Owner name: FOTOMEDIA TECHNOLOGIES, LLC, NEW HAMPSHIRE

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:IPAC ACQUISITION SUBSIDIARY I, LLC;REEL/FRAME:018362/0078

Effective date: 20060907

STCF Information on status: patent grant

Free format text: PATENTED CASE

FEPP Fee payment procedure

Free format text: PAYOR NUMBER ASSIGNED (ORIGINAL EVENT CODE: ASPN); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

AS Assignment

Owner name: FOTOMEDIA TECHNOLOGIES, LLC, NEW HAMPSHIRE

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:IPAC ACQUISITION SUBSIDIARY I, LLC;REEL/FRAME:027228/0778

Effective date: 20111114

FEPP Fee payment procedure

Free format text: PAYOR NUMBER ASSIGNED (ORIGINAL EVENT CODE: ASPN); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

Free format text: PAYER NUMBER DE-ASSIGNED (ORIGINAL EVENT CODE: RMPN); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

FPAY Fee payment

Year of fee payment: 4

AS Assignment

Owner name: KDL SCAN DESIGNS LLC, DELAWARE

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:FOTOMEDIA TECHNOLOGIES, LLC;REEL/FRAME:027512/0307

Effective date: 20111212

AS Assignment

Owner name: CHEMTRON RESEARCH LLC, DELAWARE

Free format text: MERGER;ASSIGNOR:KDL SCAN DESIGNS LLC;REEL/FRAME:036828/0702

Effective date: 20150826

FPAY Fee payment

Year of fee payment: 8

FEPP Fee payment procedure

Free format text: MAINTENANCE FEE REMINDER MAILED (ORIGINAL EVENT CODE: REM.); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

LAPS Lapse for failure to pay maintenance fees

Free format text: PATENT EXPIRED FOR FAILURE TO PAY MAINTENANCE FEES (ORIGINAL EVENT CODE: EXP.); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

STCH Information on status: patent discontinuation

Free format text: PATENT EXPIRED DUE TO NONPAYMENT OF MAINTENANCE FEES UNDER 37 CFR 1.362

FP Lapsed due to failure to pay maintenance fee

Effective date: 20200812